activity
20192024
most citedStructural block driven - enhanced convolutional neural representation for relation extraction

25 citations · 52 across the 11 of their papers we have counts for

collaborators

7 papers

cs.CR20221 cited

PMUSpill: The Counters in Performance Monitor Unit that Leak SGX-Protected Secrets

Pengfei Qiu, Yongqiang Lyu, Haixia Wang +6

Performance Monitor Unit (PMU) is a significant hardware module on the current processors, which counts the events launched by processor into a set of PMU counters. Ideally, the ev…

cs.CV20215 cited

Image Inpainting with Edge-guided Learnable Bidirectional Attention Maps

Dongsheng Wang, Chaohao Xie, Shaohui Liu +2

For image inpainting, the convolutional neural networks (CNN) in previous methods often adopt standard convolutional operator, which treats valid pixels and holes indistinguishably…

cs.CL202125 cited

Structural block driven - enhanced convolutional neural representation for relation extraction

Dongsheng Wang, Prayag Tiwari, Sahil Garg +2

In this paper, we propose a novel lightweight relation extraction approach of structural block driven - convolutional neural learning. Specifically, we detect the essential sequent…

cs.CL2020

Multi-Head Self-Attention with Role-Guided Masks

Dongsheng Wang, Casper Hansen, Lucas Chaves Lima +4

The state of the art in learning meaningful semantic representations of words is the Transformer model and its attention mechanisms. Simply put, the attention mechanisms learn to a…

cs.IR20204 cited

Denmark's Participation in the Search Engine TREC COVID-19 Challenge: Lessons Learned about Searching for Precise Biomedical Scientific Information on COVID-19

Lucas Chaves Lima, Casper Hansen, Christian Hansen +5

This report describes the participation of two Danish universities, University of Copenhagen and Aalborg University, in the international search engine competition on COVID-19 (the…

cs.CL20199 cited

MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims

Isabelle Augenstein, Christina Lioma, Dongsheng Wang +4

We contribute the largest publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification. It is collected from 26 fact checking we…